Review of Practical Propensity Score Methods Using R (Leite, 2007)

Review of Practical Propensity Score Methods Using R (Leite, 2007)
Bai, Haiyan; Pan, Wei
2017-11-17 00:00:00
psychometrika—vol. 83, no. 1, 275–278 March 2018 https://doi.org/10.1007/s11336-017-9593-6 BOOK REVIEW LEITE, W (2017). Practical Propensity Score Methods Using R. Thousand Oaks, CA: Sage Publications, p. 224, $50.00. ISBN: 978-1-4522-8888-8. How to make causal inference from quasi-experimental designs or observational studies is a key issue in social and behavioral research as well as many other ﬁelds. Propensity score methods (PSMs) (Rosenbaum & Rubin, 1983) have become popular techniques for reducing selection bias in an attempt to improve the validity of research for causal inference. In addition to many journal articles and tutorial workshops on propensity score methods, the recently published book, Practical Propensity Score Methods Using R (Leite, 2017), is a good and timely tool for promoting the practical use of PSMs in observational studies. 1. What is the Book About? Complementary to existing books on PSMs which are more theoretically based (e.g., GuoFraser, 2014; Pan & Bai, 2015), Leite’s book provides a practical guide for researchers and graduate students in the social and behavioral sciences on how to implement PSMs using the R software. The timing of the book is impeccable because it has become increasingly popular to use PSMs in observational studies. Although the literature contains a few
http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.pngPsychometrikaSpringer Journalshttp://www.deepdyve.com/lp/springer-journals/review-of-practical-propensity-score-methods-using-r-leite-2007-EMPZCKF1YH

Abstract

psychometrika—vol. 83, no. 1, 275–278 March 2018 https://doi.org/10.1007/s11336-017-9593-6 BOOK REVIEW LEITE, W (2017). Practical Propensity Score Methods Using R. Thousand Oaks, CA: Sage Publications, p. 224, $50.00. ISBN: 978-1-4522-8888-8. How to make causal inference from quasi-experimental designs or observational studies is a key issue in social and behavioral research as well as many other ﬁelds. Propensity score methods (PSMs) (Rosenbaum & Rubin, 1983) have become popular techniques for reducing selection bias in an attempt to improve the validity of research for causal inference. In addition to many journal articles and tutorial workshops on propensity score methods, the recently published book, Practical Propensity Score Methods Using R (Leite, 2017), is a good and timely tool for promoting the practical use of PSMs in observational studies. 1. What is the Book About? Complementary to existing books on PSMs which are more theoretically based (e.g., GuoFraser, 2014; Pan & Bai, 2015), Leite’s book provides a practical guide for researchers and graduate students in the social and behavioral sciences on how to implement PSMs using the R software. The timing of the book is impeccable because it has become increasingly popular to use PSMs in observational studies. Although the literature contains a few

Journal

Psychometrika
– Springer Journals

Published: Nov 17, 2017

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References

A tutorial and case study in propensity score analysis: An application to estimating the effect of in-hospital smoking cessation counseling on mortality

Austin, PC

Using propensity score analysis for making causal claims in research articles

Bai, H

Some practical guidance for the implementation of propensity score matching

Caliendo, M; Kopeinig, S

Propensity score analysis: Statistical methods and applications

Guo, SY; Fraser, MW

Practical propensity score methods using R

Leite, W

Propensity score methods in nursing research: Take advantage of them but proceed with caution

Pan, W; Bai, H

The central role of the propensity score in observational studies for causal effects

Rosenbaum, PR; Rubin, DB

Constructing a control group using multivariate matched sampling methods that incorporate the propensity score